Related Experiment Video
Updated: Jul 25, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Computational methods to predict drug safety liabilities
1Lead Safety Assessment, Bristol-Myers Squibb PRI, PO Box 4000, Princeton, NJ 08543, USA. stephen.durham@bms.com
Abstract:
Computational methods to predict drug safety liabilities are reviewed. A special emphasis of this article is on the perceived strengths and weaknesses of the commercial turnkey predictive toxicology programs (TOPKAT, MULTICASE and DEREK). This article includes proposals for improvements of individual predictive programs, experiences with pharmaceutical datasets, evaluations incorporating multiple programs, and strategies of their use as a sentinel filter for liability assessment early in the drug discovery process.
More Related Videos
16:02Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
Published on: February 10, 2023
14:34A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
Published on: April 3, 2026
Related Concept Videos
Drug Discovery: Overview
Pharmacovigilance
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Structure-Activity Relationships and Drug Design
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions
Drug Toxicity: Risk factors